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Sarina's Projects

adversarial icon adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

albert icon albert

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

albert_zh icon albert_zh

A LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS, 海量中文预训练ALBERT模型

algorithm-exercise icon algorithm-exercise

Data Structure and Algorithm notes. 数据结构与算法/leetcode/lintcode题解/

bert icon bert

TensorFlow code and pre-trained models for BERT

bert_in_keras icon bert_in_keras

在Keras下微调Bert的一些例子;some examples of bert in keras

bilm-tf icon bilm-tf

Tensorflow implementation of contextualized word representations from bi-directional language models

chinese-bert-wwm icon chinese-bert-wwm

Pre-Training with Whole Word Masking for Chinese BERT(中文BERT-wwm预训练模型)

chineseglue icon chineseglue

Language Understanding Evaluation benchmark for Chinese: datasets, baselines, pre-trained models,corpus and leaderboard

clip icon clip

Contrastive Language-Image Pretraining

cs224n icon cs224n

CS224n: Natural Language Processing with Deep Learning Assignments Winter, 2017

cs231n-2017 icon cs231n-2017

My own solutions for Stanford CS231n (2017) assignments

dalle-pytorch icon dalle-pytorch

Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

datawhale_learning icon datawhale_learning

Datawhale_Learning涵盖了AI领域从理论知识到动手实践的学习内容

dcgan-tensorflow icon dcgan-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

eda_nlp icon eda_nlp

Code for the ICLR 2019 Workshop paper: Easy data augmentation techniques for boosting performance on text classification tasks.

ernie icon ernie

An Implementation of ERNIE For Language Understanding (including Pre-training models and Fine-tuning tools)

esvit icon esvit

EsViT: Efficient self-supervised Vision Transformers

fasttext icon fasttext

Library for fast text representation and classification.

handson-ml2 icon handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

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